Evidence map›Paper›PMID 35789889›Full record

ArticleSocial network analysis and mining2022

Constant community identification in million-scale networks.

Anjan Chowdhury, Sriram Srinivasan, Sanjukta Bhowmick, Animesh Mukherjee, Kuntal Ghosh

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Social network analysis and mining, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.4field-weighted citation impact, top 44% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 2 countries.

Anjan ChowdhuryCenter for Soft Computing Research, Indian Statistical Institute, Kolkata, India.ORCID 0000-0003-1056-1568
Sriram SrinivasanDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, USA.
Sanjukta BhowmickDepartment of Computer Science, University of North Texas, Denton, USA.
Animesh MukherjeeDepartment of Computer Science and Engineering, IIT Kharagpur, Kharagpur, India.
Kuntal GhoshMachine Intelligence Unit, Indian Statistical Institute, Kolkata, India.
Indian Statistical Institute · INIndian Institute of Technology Kharagpur · INUniversity of North Texas · USVirginia Commonwealth University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The inherently stochastic nature of community detection in real-world complex networks poses an important challenge in assessing the accuracy of the results. In order to eliminate the algorithmic and implementation artifacts, it is necessary to identify the groups of vertices that are always clustered together, independent of the community detection algorithm used. Such groups of vertices are called

Indexed as

Constant communityGCNLine graphSemi-supervisedUnsupervised

Identifiers

PMID35789889
PMCPMC9243870
OpenAlexW4283746128

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.